Triple
T893385
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazil |
E19289
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Salvador |
E62572
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Salvador | Statement: [Brazil, majorCity, Salvador]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salvador Context triple: [Brazil, majorCity, Salvador]
-
A.
Salvador
Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
-
B.
Salvador, Bahia, Brazil
chosen
Salvador, the capital of Brazil’s Bahia state, is a major coastal city known for its Afro-Brazilian culture, colonial architecture, and historic role as the country’s first capital.
-
C.
Rio de Janeiro
Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
-
D.
Olinda
Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
-
E.
Belém
Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad212cd8819091eb1b7d606f5afd |
completed | March 1, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a9339ba2e48190872fd771386ba321 |
completed | March 5, 2026, 7:41 a.m. |
Created at: March 1, 2026, 7:39 p.m.